Publicly available HIV clinical data from the Women's Interagency HIV cohort Study (WIHS).
Inclusion criteria of the study were that women at enrolment were
(i) alive, (ii) HIV-1 infected, and (iii) free of clinical AIDS symptoms.
Women were followed until the first of the following occurred:
(i) treatment initiation (HAART), (ii) AIDS diagnosis, (iii) death, or administrative censoring.
The studied outcomes were the competing risks "AIDS/Death (before HAART)" and "Treatment Initiation (HAART)".
However, here, for simplification purposes, only the first of the two competing events (i.e. the time to AIDS/Death),
was used in this dataset example. Likewise, the entire study enrolled 1164 women, but only the complete cases were used
in this clinical dataset example for simplification. Variables included history of Injection Drug Use ("IDU") at enrollment,
African American ethnicity ("Race"), age ("Age"), and baseline CD4 count ("CD4"). The question in this dataset example
was whether it is possible to achieve a prognostication of patients for AIDS and HAART.
See below Bacon et al. (2005) and the WIHS website for more details.
Usage
Real.1
Format
Dataset consists of a numericdata.frame containing n=485 complete observations (samples)
by rows and p=4 clinical covariates by columns, not including the censoring indicator and (censored) time-to-event variables.
It comes as a compressed Rda data file.
Acknowledgments: This project was partially funded by the National Institutes of Health
NIH - National Cancer Institute (R01-CA160593) to J-E. Dazard and J.S. Rao.
Source
See real data application in Dazard et al., 2015.
References
Dazard J-E., Choe M., LeBlanc M. and Rao J.S. (2015).
"Cross-validation and Peeling Strategies for Survival Bump Hunting using Recursive Peeling Methods."
Statistical Analysis and Data Mining (in press).
Dazard J-E., Choe M., LeBlanc M. and Rao J.S. (2014).
"Cross-Validation of Survival Bump Hunting by Recursive Peeling Methods."
In JSM Proceedings, Survival Methods for Risk Estimation/Prediction Section. Boston, MA, USA.
American Statistical Association IMS - JSM, p. 3366-3380.
Dazard J-E., Choe M., LeBlanc M. and Rao J.S. (2015).
"R package PRIMsrc: Bump Hunting by Patient Rule Induction Method for Survival, Regression and Classification."
In JSM Proceedings, Statistical Programmers and Analysts Section. Seattle, WA, USA.
American Statistical Association IMS - JSM, (in press).
Dazard J-E. and J.S. Rao (2010).
"Local Sparse Bump Hunting."
J. Comp Graph. Statistics, 19(4):900-92.